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Argos: Enhancing Fully Homomorphic Encryption

Argos makes fully homomorphic encryption faster and more secure for real-world use.

Jules Drean, Fisher Jepsen, Edward Suh, Srini Devadas, Aamer Jaleel, Gururaj Saileshwar

― 6 min read


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Table of Contents

Fully Homomorphic Encryption (FHE) is a fancy term for a technique that allows calculations to be performed on data without needing to see the actual data itself. Imagine being able to do math with your bank information while it’s still locked in a vault. You send encrypted data to someone, they perform calculations on it, and then send back the results-all without ever seeing the original numbers. It’s like asking someone to bake a cake but only giving them the ingredients without revealing what kind of cake it is.

FHE has various potential applications, from private contact discovery (finding out which friends are using a certain app without revealing the entire contact list) to secure smart contracts that work without exposing sensitive information. However, despite all its potential, FHE has some roadblocks that researchers have been trying to overcome.

The Problem with FHE

One of the biggest challenges with FHE is that it can be quite slow. Using it might add performance costs that can range from three to even seven times slower than traditional (non-private) computing. This overhead makes FHE impractical for many real-world scenarios. Besides the speed issue, there’s a significant concern about the integrity of the data being processed. If someone maliciously tinkers with the data while it’s being computed, they could compromise the entire process.

In regular situations, if you trust the person you’re giving your data to, you might not worry too much. But in the world of FHE, we can’t always count on people being honest. This is why adding a layer of Verifiability-ensuring that the calculations done on the locked data are indeed correct-becomes essential.

Argos: A Solution to the FHE Challenges

Meet Argos, a platform designed to make FHE more user-friendly and secure. It tackles the issues of speed and security by combining trusted hardware with the principles of FHE. It’s like a trustworthy friend who can make sure your secret ingredient cake is made correctly without snooping around your recipe.

  1. Verifiability: Argos allows users to check that their computations were done correctly. This is crucial in cases where data is sensitive, and the person running the computations may not have the best of intentions.

  2. Low Overhead: Using Argos, the added time for calculations is minimal-just a few extra seconds in most cases. This makes it a viable option for applications that need privacy without sacrificing too much speed.

  3. Commodity Hardware: Argos doesn’t require fancy or expensive hardware. Instead, it works with standard processors, meaning that anyone with a regular computer can take advantage of its benefits.

  4. Side-Channel Protection: One of the significant advancements of Argos is its ability to keep secrets safe from side-channel attacks. Side-channel attacks happen when a sneaky attacker tries to gather sensitive information by observing indirect data, like timing or power usage. Argos stores secret keys in a secure area, making it tough for anyone to sneak a peek.

Why Verifiability is Key

Verifiability is like having a stamp of approval on your cake recipes. When you send your encrypted data off for calculations, you want to be sure that what comes back is genuinely what you’re expecting. If the server providing the calculations can’t be trusted, the results may be worthless, or even harmful. Argos makes sure that the evaluation was done on the right data and that the results can be believed.

In the cake analogy, it's like sending the secret ingredient list to someone for baking but also getting a note confirming that they used the exact ingredients. This is crucial, especially in scenarios where the data is sensitive.

The Use of Trusted Hardware

Using trusted hardware, like a physical Trusted Platform Module (TPM), is one of the cornerstones of Argos. This module acts like a secure vault inside your computer. It holds secret keys and performs cryptographic operations independently of the main processor, keeping the important bits away from prying eyes.

By securing the keys in this separate vault, the chances of someone stealing important information through software vulnerabilities are reduced drastically. So, instead of keeping your cake ingredients on the kitchen counter where they can be easily snatched, you lock them in a safe that only you can access.

Performance Metrics

When it comes to performance, Argos proves to be quite impressive. With a minimal overhead added to FHE evaluations, it manages to keep tasks running effectively while ensuring they are secure. The prototype of Argos has shown an average additional time of only about 6% on calculations, which is quite commendable for a technique that enhances security significantly.

In real-world applications, this means running private information retrieval (PIR) tasks or private set intersection (PSI) functions will be efficient, even with Argos ensuring security. Essentially, users don’t have to pull their hair out worrying about slowness when they use Argos.

Real-World Applications

Argos is not just a theoretical concept. It has practical applications in several fields:

  1. Private Information Retrieval (PIR):

    • In this scenario, a client can retrieve information from a database without the database owner knowing what information was requested. Argos ensures that the data being pulled is correct and that the server isn’t messing around with what’s in the database.
  2. Private Set Intersection (PSI):

    • This allows two parties to find out which items they have in common without revealing all their items to each other. Argos assures both parties that the operations were performed correctly and that no one is trying to pull a fast one with the data.
  3. Private Smart Contracts:

    • These contracts can automatically execute transactions when certain conditions are met, all while keeping sensitive information private. Argos provides the necessary security to ensure the conditions are met accurately without exposing underlying data.
  4. Secure Cloud Computing:

    • With the rise of cloud services, Argos can be used to provide secure computations in cloud environments, where users are often wary of their data being mishandled.

The Security Model of Argos

Argos operates under a specific security model. To keep everything safe, it assumes that there’s a strong adversary who might try to exploit software vulnerabilities. However, it also relies on a well-designed setup that significantly reduces the chance of exploitation.

By excluding secrets from the CPU and memory hierarchy, Argos is built on the principle that an attacker should have no way of sneaking in and stealing sensitive information if there’s nothing to steal in the first place. This is akin to keeping your cake recipe locked away so carefully that no one can even figure out what the ingredients might be.

Conclusion

In a world where data privacy is becoming increasingly important, Argos stands out as a promising solution. By marrying fully homomorphic encryption with trusted hardware and a focus on verifiability, it opens doors to various secure applications while minimizing the pains of performance overhead.

So next time you think of sharing sensitive information or performing calculations on encrypted data, you might just consider sending it through Argos-a platform that ensures your secrets remain safe while still getting the job done, almost as if there’s a magic chef baking your cake just right!

Original Source

Title: Teaching an Old Dog New Tricks: Verifiable FHE Using Commodity Hardware

Abstract: We present Argos, a simple approach for adding verifiability to fully homomorphic encryption (FHE) schemes using trusted hardware. Traditional approaches to verifiable FHE require expensive cryptographic proofs, which incur an overhead of up to seven orders of magnitude on top of FHE, making them impractical. With Argos, we show that trusted hardware can be securely used to provide verifiability for FHE computations, with minimal overhead relative to the baseline FHE computation. An important contribution of Argos is showing that the major security pitfall associated with trusted hardware, microarchitectural side channels, can be completely mitigated by excluding any secrets from the CPU and the memory hierarchy. This is made possible by focusing on building a platform that only enforces program and data integrity and not confidentiality (which is sufficient for verifiable FHE, since all data remain encrypted at all times). All secrets related to the attestation mechanism are kept in a separate coprocessor (e.g., a TPM) inaccessible to any software-based attacker. Relying on a discrete TPM typically incurs significant performance overhead, which is why (insecure) software-based TPMs are used in practice. As a second contribution, we show that for FHE applications, the attestation protocol can be adapted to only incur a fixed cost. Argos requires no dedicated hardware extensions and is supported on commodity processors from 2008 onward. Our prototype implementation introduces 6% overhead to the FHE evaluation, and 8% for more complex protocols. In particular, we show that Argos can be adapted for real-world applications of FHE, such as PIR and PSI. By demonstrating how to combine cryptography with trusted hardware, Argos paves the way for widespread deployment of FHE-based protocols beyond the semi-honest setting, without the overhead of cryptographic proofs.

Authors: Jules Drean, Fisher Jepsen, Edward Suh, Srini Devadas, Aamer Jaleel, Gururaj Saileshwar

Last Update: 2024-12-04 00:00:00

Language: English

Source URL: https://arxiv.org/abs/2412.03550

Source PDF: https://arxiv.org/pdf/2412.03550

Licence: https://creativecommons.org/licenses/by/4.0/

Changes: This summary was created with assistance from AI and may have inaccuracies. For accurate information, please refer to the original source documents linked here.

Thank you to arxiv for use of its open access interoperability.

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